title: BLEED-Myocardial Infarction Score: Predicting mid-term post-discharge bleeding events.
abstract: OBJECTIVE
  To derive and validate a score for the prediction of mid-term bleeding events following discharge for myocardial infarction (MI).
  
  
  METHODS
  One thousand and fifty patients admitted for MI and followed for 19.9 ± 6.7 mo were assigned to a derivation cohort. A new risk model, called BLEED-MI, was developed for predicting clinically significant bleeding events during follow-up (primary endpoint) and a composite endpoint of significant hemorrhage plus all-cause mortality (secondary endpoint), incorporating the following variables: age, diabetes mellitus, arterial hypertension, smoking habits, blood urea nitrogen, glomerular filtration rate and hemoglobin at admission, history of stroke, bleeding during hospitalization or previous major bleeding, heart failure during hospitalization and anti-thrombotic therapies prescribed at discharge. The BLEED-MI model was tested for calibration, accuracy and discrimination in the derivation sample and in a new, independent, validation cohort comprising 852 patients admitted at a later date.
  
  
  RESULTS
  The BLEED-MI score showed good calibration in both derivation and validation samples (Hosmer-Lemeshow test P value 0.371 and 0.444, respectively) and high accuracy within each individual patient (Brier score 0.061 and 0.067, respectively). Its discriminative performance in predicting the primary outcome was relatively high (c-statistic of 0.753 ± 0.032 in the derivation cohort and 0.718 ± 0.033 in the validation sample). Incidence of primary/secondary endpoints increased progressively with increasing BLEED-MI scores. In the validation sample, a BLEED-MI score below 2 had a negative predictive value of 98.7% (152/154) for the occurrence of a clinically significant hemorrhagic episode during follow-up and for the composite endpoint of post-discharge hemorrhage plus all-cause mortality. An accurate prediction of bleeding events was shown independently of mortality, as BLEED-MI predicted bleeding with similar efficacy in patients who did not die during follow-up: Area Under the Curve 0.703, Hosmer-Lemeshow test P value 0.547, Brier score 0.060; low-risk (BLEED-MI score 0-3) event rate: 1.2%; intermediate risk (score 4-6) event rate: 5.6%; high risk (score ≥ 7) event rate: 12.5%.
  
  
  CONCLUSIONS
  A new bedside prediction-scoring model for post-discharge mid-term bleeding has been derived and preliminarily validated. This is the first score designed to predict mid- term hemorrhagic risk in patients discharged following admission for acute MI. This model should be externally validated in larger cohorts of patients before its potential implementation.
authors.affiliation: Sérgio Barra, Rui Providência, Francisca Caetano, Inês Almeida, Luís Paiva, Paulo Dinis, António Leitão Marques, Cardiology Department, Coimbra's Hospital and University Centre-General Hospital, 3041-801 S. Martinho do Bispo, Coimbra, Portugal.
authors.forename: Sérgio
authors.initials: S
authors.lastname: Barra
authors.forename: Rui
authors.initials: R
authors.lastname: Providência
authors.forename: Francisca
authors.initials: F
authors.lastname: Caetano
authors.forename: Inês
authors.initials: I
authors.lastname: Almeida
authors.forename: Luís
authors.initials: L
authors.lastname: Paiva
authors.forename: Paulo
authors.initials: P
authors.lastname: Dinis
authors.forename: António
authors.initials: A
authors.lastname: Leitão Marques
keywords: Bleeding; Myocardial infarction; Prediction model; Risk stratification